SSC Design Team

1. Establishing An Approach for Determining Cause/Effect Relationship Between Air Pollutants And Forest Ecosystem Health in the Oil Sands Region SSC Design Team Presented to the Wood Buffalo Environmental Association- Terrestrial Environment Effects Monitoring-Science Subcommittee May 15, 2007, Calgary

2. Acknowledgements

3. Outline • Defining forest health • Fundamentals of monitoring forest health • Recommendations on the “way forward” • Gaps • Proposed new WBEA TEEM approach • System requirements • Next Steps

4. Health (human) • The Merriam Webster Dictionary defines health as “the condition of an organism with respect to the performance of its vital functions.”* • Golz, (1993)

5. Translating health to forest health • “The capacity to supply and allocate water, nutrients and energy in ways that increase or maintain productivity while maintaining resistance to biotic and abiotic stresses”* • Recommended by UNFF (2003) *McLaughlin, S., Percy, K. 1999. Forest health in North America: some perspectives on actual and potential roles of climate and air pollution. Water, Air and Soil Pollution 116: 151-197.

6. Fundamentals of monitoring forest health to detect change and determine cause/effect relationships

7. Expectations from monitoring • Is there any measurable change in forest health? • Detection • If there is, how serious is the effect and how will it progress? • Quantification • If air pollutant exposure leading to the effect is diminished, will forest health improve in the future? • Understanding processes and resilience Elzinga et al. (2001); Percy, Ferretti (2004); Ferretti, Percy (2006)

8. Conceptual Designs (1-4) • 1. Statistically - based • UNECE pan national grid • FIA in US FHM • 2. Geo-statistically - based • Probabilistic human health +spatial statistical • AOS TEEM Berryman lichens (11km, 4 directions)) • 3. Eco-region - based • Canada ARNEWS • 4. Categorically - based • WBEA TEEM AMP

9. Conceptual Designs (5-6) • 5. Gradient - based • Sudbury, Finnish Lapland Forest Damage Project • AOS TEEM Berryman lichens (11km, 4 directions) • 6. Pattern-oriented/ecologically analogous • West Whitecourt Case Study • Oxidant-San Bernardino Mts Case Study

10. What have we learned: Key messages • Monitoring and understanding the relative roles of natural and anthropogenic stress in influencing forest health will require programs that are structured to evaluate responses at appropriate frequencies across gradients of forest resources that sustain them. • Such programs must be accompanied by supplemental process-oriented investigations that more thoroughly test causes and effect relationships among stresses and responses of both forests and the biogeochemical processes that sustain them. McLaughlin and Percy (1999)

11. TEEM : recommendations in Jones (2006)

12. Recommendations on Future Monitoring* • “Given the current data set, it is not possible to de-aggregate the influences of these different factors and reach any definitive conclusions on reasons for differentiation in forest productivity on the TEEM study sites.” • “The only way to address this issue is to establish more study sites, so that conclusions on emissions effects are less reliant on the idiosyncrasies of a small number of sites” *Jones (2006)

13. Recommendations on Future Monitoring* • “Data from soils, under-story vegetation and forestry program components suggest that the 13 sites are imperfect ecological analogues, and that site and stand differences exist that may make identification of deposition impacts extremely difficult.” • “The first is to re-select sites to provide a suite of locations that are more ecologically analogous.” *Jones (2006)

14. Recommendations on Future Monitoring* • “Examination of lichen tissue elemental concentrations as bioassay air quality monitoring data suggests that modeled PAI values used in data analysis may be inaccurate.” • “It is recommended that an evaluation of these modeled data, based on empirical air-quality measurements…” *Jones (2006)

15. Significant Gaps For Determining Cause/Effect Relationship Between Air Pollutants And Forest Ecosystem Health • Co-measurement of air quality/meteorology and receptor response in space and time • Continuous pollutant monitoring outside valley • Wood Buffalo Air-shed Partnership Vision (April 12) “State of the art air monitoring system that meets the needs of residents and stakeholders in the Wood Buffalo Region” • Link with NOx/SOx

16. Significant Gaps For Determining Cause/Effect Relationship Between Air Pollutants And Forest Ecosystem Health • Emissions inventory • SO2, NOx etc • Organics • Source apportionment* • Important to TEEM mission of detecting and interpreting effects • Improve understanding of how system operates • Link back to control strategy in air-shed management *Chen et al. (2007) UNMIX and Positive Matrix Factorization

17. Proposed new system for WBEA • Key decisions • Conceptual design • Indicators • Endpoint • Plots

18. Decisions taken March 7 • requirement for forest health approach√ • retention of ecologically analogous approach√ • requirement for co-measurement in space and time of stressors and receptors√ • retention of existing plots where possible√ • inclusion of early warning as design component√ • requirement for dry and wet-exposure measurement√ • requirement for meteorological co-measurement√

19. Decisions required for detection of change and determination of cause-effect relationship • Indicators for measurement • foliar chemistry, soil ion exchange etc. • endpoint (final point) for measurement • jP productivity • relax existing stand size restrictions • abandon ARNEWS constraints • plot size, shape • requirement for emissions inventory and source-apportionment

20. TEEM Mission “The Terrestrial Environmental Effects Monitoring (TEEM) Acidification Monitoring Program of the Wood Buffalo Environmental Association (WBEA) is designed to determine if anthropogenic emissions of acidifying compounds such as SO2 and NOx gases from oil sands operations are having a long-term adverse effect on the regional terrestrial environment, and if so, to determine the magnitude of this effect. Potential adverse effects include acidification of soils from sulphur and nitrogen oxides, and detrimental impacts to vegetation, either as a direct result of exposure to emissions, or as a result of soil acidification.”

21. Shifting Our Conceptual Design • 2004 : Categorically – based • 2007 : Pattern-oriented- and Ecologically-based • appropriate frequencies across gradients of forest resources that sustain them

22. Designs for estimating change in forest resources* *modified from Scott (1998)

25. Minimizing background noise, maximizing signal *De Vries et al. (2003)

26. Stratify on patterns of stressors and forest resources

27. Number of plots • Process = 8-10 • Portable = 10-15 tower Stand edge sources 1 m 10 m Regional representation early warning

28. Enhanced plot selection opportunity: relaxed area restriction • A forest is • “a 1 ha minimum area, 25% canopy cover of trees that have the potential to reach 5 m height at maturity”. • A forest stand is • “a community of trees, including above-ground and below-ground biomass and soils, sufficiently uniform in species, composition, age, and management type” www.carbon.cfs.nrcan.gc.ca

29. Plot Selection Criteria

30. Plot Selection Criteria

31. Plot size and shape Area = 0.015 ha (154 m2) Shape = circular 14 m diameter

32. Building a forest health pyramid Forest productivity endpoint dia. mortality Insects OM decomp. CEC base saturation Process changes Modifiers Stressors Soil indicators soluble ions C/N cycling Foliar indicators physiology/biochem. Cuticle Lichens T, precip., PAR, wind, soil moisture SO2, S, NOx, O3 Early warning Physical, chemical characteristics pH, soil chemistry, drainage, slope Ecological characteristics history, tree species, density, ground veg., pests

33. TEEM Indicators

34. Prerequisites for Indicator Selection • Responsive • Indicator must respond to the stressor at some level of exposure • Specific • Predictable response to exposure from one or more stressors • Representative • Response measured is regionally representative • Robust • Responsive, specific, representative but also over time and space

35. 1. Air quality indicators • O3, SO2, H2S, NO2, NH3, HNO3, CO2 • Passives, monthly above all plots (within canopy process plots); N forms for N saturation potential • O3, SO2, NO, NO2 • Continuous, few process plots outside valley • PM • Occasionally at ≤2.5 and ≤ 10 fractions (key elements, ions) • Occult deposition • Fog chemistry within valley (pilot few sites)

36. Expand measurement of exposure/inputs Plot 205 June 7, 2006

37. 2. Meteorological indicators • Wind speed/direction • Air temperature • Relative humidity • Solar radiation • Soil temperature • 2 depths (10 and 30 cm) • Soil moisture • TDR, 2 depths • Wetness • Precipitation • Frequency, intensity, amount

38. Add measurement of meteorology/climate i.e. Hobo met stations, data loggers, sensors Not expensive, reliable, available, wireless/remote, reliable

39. 3. Above-ground indicators • Tree diameter increment • dendrometer bands; yearly; all plots • Leaf area index (LAI) • Baseline, every 3 years, all plots • Needle physicochemical condition • Yearly; wax composition process plots; droplet contact angle (DCA) portable plots; “erosion index” • Needle retention • Ocular; Yearly if met measured; all plots

40. 3. Above-ground indicators • Foliar chemistry • Tot. S, inorganic S, C/N, Ca, Mg, K, P, Mn, Cr, V, yearly (3) then less frequently (3-5) • other trace elements; select from emissions inventory • PM, organics relative retention index • Pilot; from needle physicochemical sample • Lichen vigor • Baseline, every 5 years, all plots

41. 3. Above-ground indicators • Biodiversity • Ground veg. diversity, abundance (baseline, every 5 years) • Forest health assessment • Baseline, every 5 years; all plots • Freefall, through-fall precipitation • Ion-exchange resin samplers; process plots, seasonally • Wet input with dry input for measurement of N saturation

42. 4. Soil Surface Indicators • Organic matter chemistry • PRS probes under surface organic horizon; seasonally (min 4 wks; max 1 set); process plots • Cladina/forest floor • Litter-fall • Quadrats; selected process plots; yearly? • Organic matter biomass, respiration, PLFA

43. 5. Below-ground indicators • Soil chemistry • Baseline at establishment; all plots (pH, BSAT, CA/Al); every 5-10 years • Nutrient supply rate • PRS probes seasonally (min 4 wks; max 1 set); all plots • Soil biology structure • DNA, morphology; every 5 years; process plots • Assessed in laboratory Photo from: www.westernag.ca

44. TEEM Endpoint

45. Endpoint = Jack Pine Productivity • It is a final point in a key ecosystem process • Change in processes and functions over time feedback to productivity • It can be measured with accuracy/precision over time • It is supported by published exposure-response science completed within the ambient air context • It is of social, economic or ecological importance • It can be used to support decisions on air quality management Percy, Karnosky 2007. Air quality in natural areas: interface between the public, science and regulation. Environ. Poll. (accepted)

46. Endpoint Measurement • Tree diameter • baseline at establishment; every 5 years • Tree height • baseline at establishment; every 5 years • Volume/biomass • Calculated from height/diameter • Available from remote sensing

47. System Protocols • Protocol manual required • To be developed • Sampling procedures, handling procedures • QA/QC protocols • Sampling accuracy/precision • Analytical accuracy/precision • Reporting requirement

48. System Requirements • Current plot conversion to process plots • Some relocated to include stand edge (early warning) • Some (3-5?) are not analogous and will be replaced • Towers • replace some old design (support met, passives) • install at new portable plots • Highly qualified personnel • Training, rigor, continuity

49. Next Steps • SSC decision on proposed approach • June 07- Select new candidate plots • July 07 - Visit candidate plots to confirm criteria; adjust • October 07 - Final plot selection • Nov-Dec 07 - Detailed planning for 2008 • Jan-March 08 - Procurement • May-Nov. 08 – install plots; collect data

50. Estimated costs per process plot • Tower • Met sensors, logger, wireless router ($3000) • Passives ($ ) • PRS probes ($500) • IER resins ($ ) • Dendrometer bands ($1000)